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Cataloged from SupraLabs/Supra-1.5-50M-instruct-exp-gguf
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GGUF quantizations of SupraLabs/Supra-1.5-50M-instruct-exp, an experimental 50M-parameter instruction-tuned model by SupraLabs, part of Project Chimera.
Run it entirely on CPU, low-VRAM GPUs, or embedded hardware. No cloud required.
Note: This is an experimental model. Do not use in production.
Q4_K_M— Usable, not recommended unless device is compute-constrained.
Q8_0— Perfect size/performance!.
Q2_K— ultra-constrained devices (not reccomended!).
This model uses the Alpaca Chat Format:
With optional input:
Supra-1.5-50M-instruct-exp achieves superior performance within the 50M-parameter class, with a consistent BLiMP score of 67.4.
Key findings from evaluation:
For full benchmark charts and BLiMP probe analysis, see the base model card.
Released under the Apache 2.0 License.
© SupraLabs 2026 — Project Chimera
Credit goes to @QyrouNnet-AI
# Downloadhuggingface-cli download SupraLabs/Supra-1.5-50M-instruct-exp-gguf \ --include "*.Q4_K_M.gguf" \ --local-dir ./
# Run./llama-cli \ -m supra-1.5-50m-instruct-exp-Q4_K_M.gguf \ -p "### Instruction:\nWhat is machine learning?\n\n### Response:\n" \ -n 256 \ --temp 0.7 \ --repeat-penalty 1.15ollama run hf.co/SupraLabs/Supra-1.5-50M-instruct-exp-gguf:Q4_K_Mfrom llama_cpp import Llama
llm = Llama.from_pretrained( repo_id="SupraLabs/Supra-1.5-50M-instruct-exp-gguf", filename="*Q4_K_M.gguf", n_ctx=1024, verbose=False,)
def chat(instruction: str, input_text: str = "") -> str: if input_text.strip(): prompt = ( "Below is an instruction that describes a task, paired with an input " "that provides further context. Write a response that appropriately " "completes the request.\n\n" f"### Instruction:\n{instruction}\n\n" f"### Input:\n{input_text}\n\n" "### Response:\n" ) else: prompt = ( "Below is an instruction that describes a task. Write a response that " "appropriately completes the request.\n\n" f"### Instruction:\n{instruction}\n\n" "### Response:\n" ) output = llm(prompt, max_tokens=256, temperature=0.7, top_k=50, top_p=0.9, repeat_penalty=1.15) return output["choices"][0]["text"].strip()
print(chat("Explain what artificial intelligence is."))Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:{instruction}
### Response:Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:{instruction}
### Input:{input}
### Response: